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Comment by hallman76 | Hacker News Reader

We developed a web-based tool that described water quality based on your location. We generated screenshots of every outcome so the results could be shared to FB/titter. It was something on the order of 40k screenshots. Our process used headless chrome to generate a screenshot then it was uploaded to S3 for hosting.

Doing that in a series took forever. It took something like 14 hours to generate the screenshots, then 4 hours to upload them all. Spreading that load across lambda functions allowed us to basically run the job in parallel. Each individual lambda process took longer to generate a screenshot than on our initial desktop process, but the overall process was dramatically faster.

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The parallelism argument doesn’t pass muster because you can do the same thing with a cluster of free tier t2.micro machines with any good orchestration platform, not just lambda.

This argument is basically: no counterpoint to the original post, but you can do things that are also easy on any other comparable platform.

Tell me again what I don’t understand?

> you can do the same thing with a cluster of free tier t2.micro machines

Not if you already used your free tier. Lambda is X free per month. Free tier t2.micro is X free for first 12 months.

> Tell me again what I don’t understand?

As someone who has done both, it's far, far easier to stand up a lambda than it is to manage a cluster of servers.

This still doesn’t make sense. There are portable systems that do the same, and have fully managed options, such as kubernetes.

In my mind the thing that makes lambda “easier” is they make a bunch of decisions for you, for better or worse. For real applications probably for the worse. If you have the knowledge to make those decisions for yourself you’re probably better off doing that.

> This still doesn’t make sense. There are portable systems that do the same, and have fully managed options, such as kubernetes.

The whole value proposition behind AWS is that they can do it better than your business due (directly or indirectly) to economies of scale. I think Kubernetes is super cool, but rebuilding AWS on top of Kubernetes is not cost effective for most companies--they're better off using AWS-managed offerings. Of course, you can mix and match via EKS or similar, but there are lots of gotchas there as well (how do I integrate Kubernetes' permissions model with IAM? how do I get Kubernetes logs into CloudWatch? how do I use CloudWatch to monitor Kubernetes events? etc).

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